[HTML][HTML] Artificial intelligence for cybersecurity: Literature review and future research directions
R Kaur, D Gabrijelčič, T Klobučar - Information Fusion, 2023 - Elsevier
Artificial intelligence (AI) is a powerful technology that helps cybersecurity teams automate
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
repetitive tasks, accelerate threat detection and response, and improve the accuracy of their …
A review of anomaly detection strategies to detect threats to cyber-physical systems
N Jeffrey, Q Tan, JR Villar - Electronics, 2023 - mdpi.com
Cyber-Physical Systems (CPS) are integrated systems that combine software and physical
components. CPS has experienced rapid growth over the past decade in fields as disparate …
components. CPS has experienced rapid growth over the past decade in fields as disparate …
A review on attack graph analysis for iot vulnerability assessment: challenges, open issues, and future directions
OSMBH Almazrouei, P Magalingam, MK Hasan… - IEEE …, 2023 - ieeexplore.ieee.org
Vulnerability assessment in industrial IoT networks is critical due to the evolving nature of
the domain and the increasing complexity of security threats. This study aims to address the …
the domain and the increasing complexity of security threats. This study aims to address the …
SHARKS: Smart hacking approaches for risk scanning in Internet-of-Things and cyber-physical systems based on machine learning
Cyber-physical systems (CPS) and Internet-of-Things (IoT) devices are increasingly being
deployed across multiple functionalities, ranging from healthcare devices and wearables to …
deployed across multiple functionalities, ranging from healthcare devices and wearables to …
Machine learning assisted security analysis of 5g-network-connected systems
The core network architecture of telecommunication systems has undergone a paradigm
shift in the fifth-generation (5G) networks. 5G networks have transitioned to software-defined …
shift in the fifth-generation (5G) networks. 5G networks have transitioned to software-defined …
AI-enabled IoT penetration testing: state-of-the-art and research challenges
ABSTRACT Internet of Things (IoT) is gaining importance as its applications are found in
many critical infrastructure sectors (eg, Industry 4.0, healthcare, transportation, and …
many critical infrastructure sectors (eg, Industry 4.0, healthcare, transportation, and …
[HTML][HTML] A hybrid XSS attack (HYXSSA) based on fusion approach: Challenges, threats and implications in cybersecurity
Cross-site scripting (XSS) attacks have been extensively studied in the literature, although
mitigating such attacks remain a challenge for cyber defenders. In this paper, we survey the …
mitigating such attacks remain a challenge for cyber defenders. In this paper, we survey the …
Enhancing Security in Cloud Computing Using Artificial Intelligence (AI)
D Stutz, JT de Assis, AA Laghari… - … Analytics and Cyber …, 2024 - Wiley Online Library
Cloud computing (CC) technologies (viz artificial intelligence (AI), data science,
blockchain,“big data”(BD), etc.) are progressively widespread and practically applied …
blockchain,“big data”(BD), etc.) are progressively widespread and practically applied …
ML-FEED: Machine Learning Framework for Efficient Exploit Detection
Machine learning (ML)-based methods have recently become attractive for detecting
security vulnerability exploits. Unfortunately, state-of-the-art ML models like long short-term …
security vulnerability exploits. Unfortunately, state-of-the-art ML models like long short-term …
Uncovering the Risk of Academic Information System Vulnerability through PTES and OWASP Method
FP Utama, RMH Nurhadi - CommIT (Communication and …, 2024 - journal.binus.ac.id
The security of academic information systems needs consideration to anticipate various
threats, resulting in data leakage, misuse of information, modification, and data destruction …
threats, resulting in data leakage, misuse of information, modification, and data destruction …